Effective and structural connectivity in the human auditory cortex

Neural Functioning in Late-Life Depression: An Activation Likelihood Estimation Meta-Analysis

Late-life depression (LLD) is a relatively common and debilitating mental disorder, also associated with cognitive dysfunctions and an increased risk of mortality. Considering the growing elderly population worldwide, LLD is increasingly emerging as a significant public health issue, also due to the rise in direct and indirect costs borne by healthcare systems. Understanding the neuroanatomical and neurofunctional correlates of LLD is crucial for developing more targeted and effective interventions, both from a preventive and therapeutic standpoint. This ALE meta-analysis aims to evaluate the involvement of specific neurofunctional changes in the neurophysiopathology of LLD by analysing functional neuroimaging studies conducted on patients with LLD compared to healthy subjects (HCs). We included 19 studies conducted on 844 subjects, divided into 439 patients with LLD and 405 HCs. Patients with LLD, compared to HCs, showed significant hypoactivation of the right superior and medial frontal gyri (Brodmann areas (Bas) 8, 9), left cingulate cortex (BA 24), left putamen, and left caudate body. The same patients exhibited significant hyperactivation of the left superior temporal gyrus (BA 42), left inferior frontal gyrus (BA 45), right anterior cingulate cortex (BA 24), right cerebellar culmen, and left cerebellar declive. In summary, we found significant changes in activation patterns and brain functioning in areas encompassed in the cortico-limbic-striatal network in LLD. Furthermore, our results suggest a potential role for areas within the cortico-striatal-cerebellar network in the neurophysiopathology of LLD.

Comprehensive behavioral and physiologic assessment of peripheral and central auditory function in individuals with mild traumatic brain injury

Auditory complaints are frequently reported by individuals with mild traumatic brain injury (mTBI) yet remain difficult to detect in the absence of clinically significant hearing loss. This highlights a growing need to identify sensitive indices of auditory-related mTBI pathophysiology beyond pure-tone thresholds for improved hearing healthcare diagnosis and treatment. Given the heterogeneity of mTBI etiology and the diverse peripheral and central processes required for normal auditory function, the present study sought to determine the audiologic assessments sensitive to mTBI pathophysiology at the group level using a well-rounded test battery of both peripheral and central auditory system function. This test battery included pure-tone detection thresholds, word understanding in quiet, sentence understanding in noise, distortion product otoacoustic emissions (DPOAEs), middle-ear muscle reflexes (MEMRs), and auditory evoked potentials (AEPs), including auditory brainstem responses (ABRs), middle latency responses (MLRs), and late latency responses (LLRs). Each participant also received magnetic resonance imaging (MRI). Compared to the control group, we found that individuals with mTBI had reduced DPOAE amplitudes that revealed a compound effect of age, elevated MEMR thresholds for an ipsilateral broadband noise elicitor, longer ABR Wave I latencies for click and 4 kHz tone burst elicitors, longer ABR Wave III latencies for 4 kHz tone bursts, larger MLR Na and Nb amplitudes, smaller MLR Pb amplitudes, longer MLR Pa latencies, and smaller LLR N1 amplitudes for older individuals with mTBI. Further, mTBI individuals with combined hearing difficulty and noise sensitivity had a greater number of deficits on thalamic and cortical AEP measures compared to those with only one/no self-reported auditory symptoms. This finding was corroborated with MRI, which revealed significant structural differences in the auditory cortical areas of mTBI participants who reported combined hearing difficulty and noise sensitivity, including an enlargement of left transverse temporal gyrus (TTG) and bilateral planum polare (PP). These findings highlight the need for continued investigations toward identifying individualized audiologic assessments and treatments that are sensitive to mTBI pathophysiology.

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Understanding central auditory processing critically depends on defining underlying auditory cortical networks and their relationship to the rest of the brain. We addressed these questions using resting state functional connectivity derived from human intracranial electroencephalography. Mapping recording sites into a low-dimensional space where proximity represents functional similarity revealed a hierarchical organization. At a fine scale, a group of auditory cortical regions excluded several higher-order auditory areas and segregated maximally from the prefrontal cortex. On mesoscale, the proximity of limbic structures to the auditory cortex suggested a limbic stream that parallels the classically described ventral and dorsal auditory processing streams. Identities of global hubs in anterior temporal and cingulate cortex depended on frequency band, consistent with diverse roles in semantic and cognitive processing. On a macroscale, observed hemispheric asymmetries were not specific for speech and language networks. This approach can be applied to multivariate brain data with respect to development, behavior, and disorders.

Localizing and lateralizing value of auditory phenomena in seizures

BACKGROUND

Auditory seizures (AS) are a rare type of focal seizures. AS are classically thought to involve a seizure onset zone (SOZ) in the temporal lobe, but there remain uncertainties about their localizing and lateralizing value. We conducted a narrative literature review with the aim of providing an up-to-date description of the lateralizing and localizing value of AS.

METHODS

The databases PubMed, Scopus, and Google Scholar were searched for literature on AS in December 2022. All cortical stimulation studies, case reports, and case series were analyzed to assess for auditory phenomena that were suggestive of AS and to evaluate if the lateralization and/or localization of the SOZ could be determined. We classified AS according to their semiology (e.g., simple hallucination versus complex hallucination) and the level of evidence with which the SOZ could be predicted.

RESULTS

A total of 174 cases comprising 200 AS were analyzed from 70 articles. Across all studies, the SOZ of AS were more often in the left (62%) than in the right (38%) hemisphere. AS heard bilaterally followed this trend. Unilaterally heard AS were more often due to a SOZ in the contralateral hemisphere (74%), although they could also be ipsilateral (26%). The SOZ for AS was not limited to the auditory cortex, nor to the temporal lobe. The areas more frequently involved in the temporal lobe were the superior temporal gyrus (STG) and mesiotemporal structures. Extratemporal locations included parietal, frontal, insular, and rarely occipital structures.

CONCLUSION

Our review highlighted the complexity of AS and their importance in the identification of the SOZ. Due to the limited data and heterogeneous presentation of AS in the literature, the patterns associated with different AS semiologies warrant further research.

Distinct neural encoding of glimpsed and masked speech in multitalker situations

Humans can easily tune in to one talker in a multitalker environment while still picking up bits of background speech; however, it remains unclear how we perceive speech that is masked and to what degree non-target speech is processed. Some models suggest that perception can be achieved through glimpses, which are spectrotemporal regions where a talker has more energy than the background. Other models, however, require the recovery of the masked regions. To clarify this issue, we directly recorded from primary and non-primary auditory cortex (AC) in neurosurgical patients as they attended to one talker in multitalker speech and trained temporal response function models to predict high-gamma neural activity from glimpsed and masked stimulus features. We found that glimpsed speech is encoded at the level of phonetic features for target and non-target talkers, with enhanced encoding of target speech in non-primary AC. In contrast, encoding of masked phonetic features was found only for the target, with a greater response latency and distinct anatomical organization compared to glimpsed phonetic features. These findings suggest separate mechanisms for encoding glimpsed and masked speech and provide neural evidence for the glimpsing model of speech perception.

Auditory attention decoding from EEG-based Mandarin speech envelope reconstruction

In the cocktail party circumstance, the human auditory system extracts the information from a specific speaker of interest and ignores others. Many studies have focused on auditory attention decoding (AAD), but the stimulation materials were mainly non-tonal languages. We used a tonal language (Mandarin) as the speech stimulus and constructed a Long Short-Term Memory (LSTM) architecture for speech envelope reconstruction based on electroencephalogram (EEG) data. The correlation coefficient between the reconstructed and candidate envelopes was calculated to determine the subject's auditory attention. The proposed LSTM architecture outperformed the linear models. The average decoding accuracy in cross-subject and inter-subject cases varies from 63.02 to 74.29%, with the highest accuracy rate of 89.1% in a decision window of 0.15 s. In addition, the beta-band rhythm was found to play an essential role in identifying the attention and the non-attention state. These results provide a new AAD architecture to help develop neuro-steered hearing devices, especially for tonal languages.

Gamma Activation and Alpha Suppression within Human Auditory Cortex during a Speech Classification Task

The dynamics of information flow within the auditory cortical hierarchy associated with speech processing and the emergence of hemispheric specialization remain incompletely understood. To study these questions with high spatiotemporal resolution, intracranial recordings in 29 human neurosurgical patients of both sexes were obtained while subjects performed a semantic classification task. Neural activity was recorded from posteromedial portion of Heschl's gyrus (HGPM) and anterolateral portion of Heschl's gyrus (HGAL), planum temporale (PT), planum polare, insula, and superior temporal gyrus (STG). Responses to monosyllabic words exhibited early gamma power increases and a later suppression of alpha power, envisioned to represent feedforward activity and decreased feedback signaling, respectively. Gamma activation and alpha suppression had distinct magnitude and latency profiles. HGPM and PT had the strongest gamma responses with shortest onset latencies, indicating that they are the earliest auditory cortical processing stages. The origin of attenuated top-down influences in auditory cortex, as indexed by alpha suppression, was in STG and HGAL. Gamma responses and alpha suppression were typically larger to nontarget words than tones. Alpha suppression was uniformly greater to target versus nontarget stimuli. Hemispheric bias for words versus tones and for target versus nontarget words, when present, was left lateralized. Better task performance was associated with increased gamma activity in the left PT and greater alpha suppression in HGPM and HGAL bilaterally. The prominence of alpha suppression during semantic classification and its accessibility for noninvasive electrophysiologic studies suggests that this measure is a promising index of auditory cortical speech processing.SIGNIFICANCE STATEMENT Understanding the dynamics of cortical speech processing requires the use of active tasks. This is the first comprehensive intracranial electroencephalography study to examine cortical activity within the superior temporal plane, lateral superior temporal gyrus, and the insula during a semantic classification task. Distinct gamma activation and alpha suppression profiles clarify the functional organization of feedforward and feedback processing within the auditory cortical hierarchy. Asymmetries in cortical speech processing emerge at early processing stages. Relationships between cortical activity and task performance are interpreted in the context of current models of speech processing. Results lay the groundwork for iEEG studies using connectivity measures of the bidirectional information flow within the auditory processing hierarchy.

Intra-individual Reliability of Voice- and Music-elicited Responses and their Modulation by Expertise

A growing number of functional neuroimaging studies have identified regions within the temporal lobe, particularly along the planum polare and planum temporale, that respond more strongly to music than other types of acoustic stimuli, including voice. This "music preferred" regions have been reported using a variety of stimulus sets, paradigms and analysis approaches and their consistency across studies confirmed through meta-analyses. However, the critical question of intra-subject reliability of these responses has received less attention. Here, we directly assessed this important issue by contrasting brain responses to musical vs. vocal stimuli in the same subjects across three consecutive fMRI runs, using different types of stimuli. Moreover, we investigated whether these music- and voice-preferred responses were reliably modulated by expertise. Results demonstrated that music-preferred activity previously reported in temporal regions, and its modulation by expertise, exhibits a high intra-subject reliability. However, we also found that activity in some extra-temporal regions, such as the precentral and middle frontal gyri, did depend on the particular stimuli employed, which may explain why these are less consistently reported in the literature. Taken together, our findings confirm and extend the notion that specific regions in the brain consistently respond more strongly to certain socially-relevant stimulus categories, such as faces, voices and music, but that some of these responses appear to depend, at least to some extent, on the specific features of the paradigm employed.

Common principles in the lateralisation of auditory cortex structure and function for vocal communication in primates and rodents

This review summarises recent findings on the lateralisation of communicative sound processing in the auditory cortex (AC) of humans, non-human primates, and rodents. Functional imaging in humans has demonstrated a left hemispheric preference for some acoustic features of speech, but it is unclear to which degree this is caused by bottom-up acoustic feature selectivity or top-down modulation from language areas. Although non-human primates show a less pronounced functional lateralisation in AC, the properties of AC fields and behavioral asymmetries are qualitatively similar. Rodent studies demonstrate microstructural circuits that might underlie bottom-up acoustic feature selectivity in both hemispheres. Functionally, the left AC in the mouse appears to be specifically tuned to communication calls, whereas the right AC may have a more 'generalist' role. Rodents also show anatomical AC lateralisation, such as differences in size and connectivity. Several of these functional and anatomical characteristics are also lateralized in human AC. Thus, complex vocal communication processing shares common features among rodents and primates. We argue that a synthesis of results from humans, non-human primates, and rodents is necessary to identify the neural circuitry of vocal communication processing. However, data from different species and methods are often difficult to compare. Recent advances may enable better integration of methods across species. Efforts to standardise data formats and analysis tools would benefit comparative research and enable synergies between psychological and biological research in the area of vocal communication processing.

Bridging the Gap Between Neurons and Cognition Through Assemblies of Neurons

During recent decades, our understanding of the brain has advanced dramatically at both the cellular and molecular levels and at the cognitive neurofunctional level; however, a huge gap remains between the microlevel of physiology and the macrolevel of cognition. We propose that computational models based on assemblies of neurons can serve as a blueprint for bridging these two scales. We discuss recently developed computational models of assemblies that have been demonstrated to mediate higher cognitive functions such as the processing of simple sentences, to be realistically realizable by neural activity, and to possess general computational power.

Parallel and distributed encoding of speech across human auditory cortex

Speech perception is thought to rely on a cortical feedforward serial transformation of acoustic into linguistic representations. Using intracranial recordings across the entire human auditory cortex, electrocortical stimulation, and surgical ablation, we show that cortical processing across areas is not consistent with a serial hierarchical organization. Instead, response latency and receptive field analyses demonstrate parallel and distinct information processing in the primary and nonprimary auditory cortices. This functional dissociation was also observed where stimulation of the primary auditory cortex evokes auditory hallucination but does not distort or interfere with speech perception. Opposite effects were observed during stimulation of nonprimary cortex in superior temporal gyrus. Ablation of the primary auditory cortex does not affect speech perception. These results establish a distributed functional organization of parallel information processing throughout the human auditory cortex and demonstrate an essential independent role for nonprimary auditory cortex in speech processing.

Auditory cortical micro-networks show differential connectivity during voice and speech processing in humans

The temporal voice areas (TVAs) in bilateral auditory cortex (AC) appear specialized for voice processing. Previous research assumed a uniform functional profile for the TVAs which are broadly spread along the bilateral AC. Alternatively, the TVAs might comprise separate AC nodes controlling differential neural functions for voice and speech decoding, organized as local micro-circuits. To investigate micro-circuits, we modeled the directional connectivity between TVA nodes during voice processing in humans while acquiring brain activity using neuroimaging. Results show several bilateral AC nodes for general voice decoding (speech and non-speech voices) and for speech decoding in particular. Furthermore, non-hierarchical and differential bilateral AC networks manifest distinct excitatory and inhibitory pathways for voice and speech processing. Finally, while voice and speech processing seem to have distinctive but integrated neural circuits in the left AC, the right AC reveals disintegrated neural circuits for both sounds. Altogether, we demonstrate a functional heterogeneity in the TVAs for voice decoding based on local micro-circuits.

Plis de passage in the superior temporal sulcus: Morphology and local connectivity

While there is a profusion of functional investigations involving the superior temporal sulcus (STS), our knowledge of the anatomy of this sulcus is still limited by a large individual variability. In particular, an accurate characterization of the "plis de passage" (PPs), annectant gyri inside the fold, is lacking to explain this variability. Performed on 90 subjects of the HCP database, our study revealed that PPs constitute landmarks that can be identified from the geometry of the STS walls. They were found associated with a specific U-shape white-matter connectivity between the two banks of the sulcus, the amount of connectivity being related to the depth of the PPs. These findings raise new hypotheses regarding the spatial organization of PPs, the relation between cortical anatomy and structural connectivity, as well as the possible role of PPs in the regional functional organization.

The extended Granger causality analysis for Hodgkin-Huxley neuronal models

How to extract directions of information flow in dynamical systems based on empirical data remains a key challenge. The Granger causality (GC) analysis has been identified as a powerful method to achieve this capability. However, the framework of the GC theory requires that the dynamics of the investigated system can be statistically linearized; i.e., the dynamics can be effectively modeled by linear regressive processes. Under such conditions, the causal connectivity can be directly mapped to the structural connectivity that mediates physical interactions within the system. However, for nonlinear dynamical systems such as the Hodgkin-Huxley (HH) neuronal circuit, the validity of the GC analysis has yet been addressed; namely, whether the constructed causal connectivity is still identical to the synaptic connectivity between neurons remains unknown. In this work, we apply the nonlinear extension of the GC analysis, i.e., the extended GC analysis, to the voltage time series obtained by evolving the HH neuronal network. In addition, we add a certain amount of measurement or observational noise to the time series to take into account the realistic situation in data acquisition in the experiment. Our numerical results indicate that the causal connectivity obtained through the extended GC analysis is consistent with the underlying synaptic connectivity of the system. This consistency is also insensitive to dynamical regimes, e.g., a chaotic or non-chaotic regime. Since the extended GC analysis could in principle be applied to any nonlinear dynamical system as long as its attractor is low dimensional, our results may potentially be extended to the GC analysis in other settings.

Functional Connectivity of Heschl's Gyrus Associated With Age-Related Hearing Loss: A Resting-State fMRI Study

A large proportion of older adults experience hearing loss. Yet, the impact of hearing loss on the aging brain, particularly on large-scale brain networks that support cognition and language, is relatively unknown. We used resting-state functional magnetic resonance imaging (fMRI) to identify hearing loss-related changes in the functional connectivity of primary auditory cortex to determine if these changes are distinct from age and cognitive measures known to decline with age (e.g., working memory and processing speed). We assessed the functional connectivity of Heschl's gyrus in 31 older adults (60-80 years) who expressed a range of hearing abilities from normal hearing to a moderate hearing loss. Our results revealed that both left and right Heschl's gyri were significantly connected to regions within auditory, sensorimotor, and visual cortices, as well as to regions within the cingulo-opercular network known to support attention. Participant age, working memory, and processing speed did not significantly correlate with any connectivity measures once variance due to hearing loss was removed. However, hearing loss was associated with increased connectivity between right Heschl's gyrus and the dorsal anterior cingulate in the cingulo-opercular network even once variance due to age, working memory, and processing speed was removed. This greater connectivity was not driven by high frequency hearing loss, but rather by hearing loss measured in the 0.5-2 kHz range, particularly in the left ear. We conclude that hearing loss-related differences in functional connectivity in older adults are distinct from other aging-related differences and provide insight into a possible neural mechanism of compensation for hearing loss in older adults.

Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces

OBJECTIVE

This paper argues that Brain-Inspired Spiking Neural Network (BI-SNN) architectures can learn and reveal deep in time-space functional and structural patterns from spatio-temporal data. These patterns can be represented as deep knowledge, in a partial case in the form of deep spatio-temporal rules. This is a promising direction for building new types of Brain-Computer Interfaces called Brain-Inspired Brain-Computer Interfaces (BI-BCI). A theoretical framework and its experimental validation on deep knowledge extraction and representation using SNN are presented.

RESULTS

The proposed methodology was applied in a case study to extract deep knowledge of the functional and structural organisation of the brain's neural network during the execution of a Grasp and Lift task. The BI-BCI successfully extracted the neural trajectories that represent the dorsal and ventral visual information processing streams as well as its connection to the motor cortex in the brain. Deep spatiotemporal rules on functional and structural interaction of distinct brain areas were then used for event prediction in BI-BCI.

SIGNIFICANCE

The computational framework can be used for unveiling the topological patterns of the brain and such knowledge can be effectively used to enhance the state-of-the-art in BCI.

Organization of extrastriate and temporal cortex in chimpanzees compared to humans and macaques

There is evidence for enlargement of association cortex in humans compared to other primate species. Expansion of temporal association cortex appears to have displaced extrastriate cortex posteriorly and inferiorly in humans compared to macaques. However, the details of the organization of these recently expanded areas are still being uncovered. Here, we used diffusion tractography to examine the organization of extrastriate and temporal association cortex in chimpanzees, humans, and macaques. Our goal was to characterize the organization of visual and auditory association areas with respect to their corresponding primary areas (primary visual cortex and auditory core) in humans and chimpanzees. We report three results: (1) Humans, chimpanzees, and macaques show expected retinotopic organization of primary visual cortex (V1) connectivity to V2 and to areas immediately anterior to V2; (2) In contrast to macaques, chimpanzee and human V1 shows apparent connectivity with lateral, inferior, and anterior temporal regions, beyond the retinotopically organized extrastriate areas; (3) Also in contrast to macaques, chimpanzee and human auditory core shows apparent connectivity with temporal association areas, with some important differences between humans and chimpanzees. Diffusion tractography reconstructs diffusion patterns that reflect white matter organization, but does not definitively represent direct anatomical connectivity. Therefore, it is important to recognize that our findings are suggestive of species differences in long-distance white matter organization rather than demonstrations of direct connections. Our data support the conclusion that expansion of temporal association cortex, and the resulting posterior displacement of extrastriate cortex, occurred in the human lineage after its separation from the chimpanzee lineage. It is possible, however, that some expansion of the temporal lobe occurred prior to the separation of humans and chimpanzees, reflected in the reorganization of long white matter tracts in the temporal lobe that connect occipital areas to the fusiform gyrus, middle temporal gyrus, and anterior temporal lobe.

Linking structural and effective brain connectivity: structurally informed Parametric Empirical Bayes (si-PEB)

Despite the potential for better understanding functional neuroanatomy, the complex relationship between neuroimaging measures of brain structure and function has confounded integrative, multimodal analyses of brain connectivity. This is particularly true for task-related effective connectivity, which describes the causal influences between neuronal populations. Here, we assess whether measures of structural connectivity may usefully inform estimates of effective connectivity in larger scale brain networks. To this end, we introduce an integrative approach, capitalising on two recent statistical advances: Parametric Empirical Bayes, which provides group-level estimates of effective connectivity, and Bayesian model reduction, which enables rapid comparison of competing models. Crucially, we show that structural priors derived from high angular resolution diffusion imaging on a dynamic causal model of a 12-region network-based on functional MRI data from the same subjects-substantially improve model evidence (posterior probability 1.00). This provides definitive evidence that structural and effective connectivity depend upon each other in mediating distributed, large-scale interactions in the brain. Furthermore, this work offers novel perspectives for understanding normal brain architecture and its disintegration in clinical conditions.

Establishing the cognitive signature of human brain networks derived from structural and functional connectivity

Numerous neuroimaging studies have identified various brain networks using task-free analyses. While these networks undoubtedly support higher cognition, their precise functional characteristics are rarely probed directly. The frontal, temporal, and parietal lobes contain the majority of the tertiary association cortex, which are key substrates for higher cognition including executive function, language, memory, and attention. Accordingly, we established the cognitive signature of a set of contrastive brain networks on the main tertiary association cortices, identified in two task-independent datasets. Using graph-theory analysis, we revealed multiple networks across the frontal, temporal, and parietal cortex, derived from structural and functional connectivity. The patterns of network activity were then investigated using three task-active fMRI datasets to generate the functional profiles of the identified networks. We employed representational dissimilarity analysis on these functional data to quantify and compare the representational characteristics of the networks. Our results demonstrated that the topology of the task-independent networks was strongly associated with the patterns of network activity in the task-active fMRI. Our findings establish a direct relationship between the brain networks identified from task-free datasets and higher cognitive functions including cognitive control, language, memory, visuospatial function, and perception. Not only does this study support the widely held view that higher cognitive functions are supported by widespread, distributed cortical networks, but also it elucidates a methodological approach for formally establishing their relationship.

Global structural integrity and effective connectivity in patients with disorders of consciousness

BACKGROUND

Previous studies have separately reported impaired functional, structural, and effective connectivity in patients with disorders of consciousness (DOC). The perturbational complexity index (PCI) is a transcranial magnetic stimulation (TMS) derived marker of effective connectivity. The global fractional anisotropy (FA) is a marker of structural integrity. Little is known about how these parameters are related to each other.

OBJECTIVE

We aimed at testing the relationship between structural integrity and effective connectivity.

METHODS

We assessed 23 patients with severe brain injury more than 4 weeks post-onset, leading to DOC or locked-in syndrome, and 14 healthy subjects. We calculated PCI using repeated single pulse TMS coupled with high-density electroencephalography, and used it as a surrogate of effective connectivity. Structural integrity was measured using the global FA, derived from diffusion weighted imaging. We used linear regression modelling to test our hypothesis, and computed the correlation between PCI and FA in different groups.

RESULTS

Global FA could predict 74% of PCI variance in the whole sample and 56% in the patients' group. No other predictors (age, gender, time since onset, behavioural score) improved the models. FA and PCI were correlated in the whole population (r = 0.86, p < 0.0001), the patients, and the healthy subjects subgroups.

CONCLUSION

We here demonstrated that effective connectivity correlates with structural integrity in brain-injured patients. Increased structural damage level decreases effective connectivity, which could prevent the emergence of consciousness.

A contemporary framework of language processing in the human brain in the context of preoperative and intraoperative language mapping

INTRODUCTION

The emergence of advanced in vivo neuroimaging methods has redefined the understanding of brain function with a shift from traditional localizationist models to more complex and widely distributed neural networks. In human language processing, the traditional localizationist models of Wernicke and Broca have fallen out of favor for a dual-stream processing system involving complex networks organized over vast areas of the dominant hemisphere. The current review explores the cortical function and white matter connections of human language processing, as well as their relevance to surgical planning.

METHODS

We performed a systematic review of the literature with narrative data analysis.

RESULTS

Although there is significant heterogeneity in the literature over the past century of exploration, modern evidence provides new insight into the true cortical function and white matter anatomy of human language. Intraoperative data and postoperative outcome studies confirm a widely distributed language network extending far beyond the traditional cortical areas of Wernicke and Broca.

CONCLUSIONS

The anatomic distribution of language networks, based on current theories, is explored to present a modern and clinically relevant interpretation of language function. Within this framework, we present current knowledge regarding the known effects of damage to both cortical and subcortical components of these language networks. Ideally, we hope this framework will provide a common language for which to base future clinical studies in human language function.

Interaction of language, auditory and memory brain networks in auditory verbal hallucinations

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The language, auditory and memory/limbic networks are of particular relevance for auditory verbal hallucinations.

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An increased interaction among the auditory-language and striatal brain regions occurs while patients hallucinate.

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Fronto-temporal connections are often altered in AVH individuals, but there is no consensus regarding increase or decrease.

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Connections of the interhemispheric auditory pathway are stronger for first episode patients, but they are weaker in chronic patients.

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The majority of studies support hybrid AVH hypotheses in which all three networks and the striatal network are involved.

Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses.

Grey matter connectivity within and between auditory, language and visual systems in prelingually deaf adolescents

PURPOSE

Previous studies have shown brain reorganizations after early deprivation of auditory sensory. However, changes of grey matter connectivity have not been investigated in prelingually deaf adolescents yet. In the present study, we aimed to investigate changes of grey matter connectivity within and between auditory, language and visual systems in prelingually deaf adolescents.

METHODS

We recruited 16 prelingually deaf adolescents and 16 age-and gender-matched normal controls, and extracted the grey matter volume as the structural characteristic from 14 regions of interest involved in auditory, language or visual processing to investigate the changes of grey matter connectivity within and between auditory, language and visual systems. Sparse inverse covariance estimation (SICE) was utilized to construct grey matter connectivity between these brain regions.

RESULTS

The results show that prelingually deaf adolescents present weaker grey matter connectivity within auditory and visual systems, and connectivity between language and visual systems declined. Notably, significantly increased brain connectivity was found between auditory and visual systems in prelingually deaf adolescents.

CONCLUSIONS

Our results indicate "cross-modal" plasticity after deprivation of the auditory input in prelingually deaf adolescents, especially between auditory and visual systems. Besides, auditory deprivation and visual deficits might affect the connectivity pattern within language and visual systems in prelingually deaf adolescents.

Neural Basis of Language: An Overview of An Evolving Model

The neural basis of language had been considered as a simple model consisting of the Broca’s area, the Wernicke’s area, and the arcuate fasciculus (AF) connecting the above two cortical areas. However, it has grown to a larger and more complex model based upon recent advancements in neuroscience such as precise imaging studies of aphasic patients, diffusion tensor imaging studies, functional magnetic resonance imaging studies, and electrophysiological studies with cortical and subcortical stimulation during awake surgery. In the present model, language is considered to be processed through two distinct pathways, the dorsal stream and the ventral stream. The core of the dorsal stream is the superior longitudinal fasciculus/AF, which is mainly associated with phonological processing. On the other hand, semantic processing is done mainly with the ventral stream consisting of the inferior fronto-occipital fasciculus and the intratemporal networks. The frontal aslant tract has recently been named the deep frontal tract connecting the supplementary motor area and the Broca’s area and it plays an important role in driving and initiating speech. It is necessary for every neurosurgeon to have basic knowledge of the neural basis of language. This knowledge is essential to plan safer surgery and preserve the above neural structures during surgery.

Evidence for normal letter-sound integration, but altered language pathways in a case of recovered Landau-Kleffner Syndrome

Landau-Kleffner Syndrome (LKS) is a rare form of acquired aphasia in children, characterized by epileptic discharges, which occur mostly during sleep. After normal speech and language development, aphasia develops between the ages of 3-7 years in a period ranging from days to months. The epileptic discharges usually disappear after reaching adulthood, but language outcomes are usually poor if no treatment focused on restoration of (non-) verbal communication is given. Patients often appear deaf-mute, but sign language, as part of the treatment, may lead to recovery of communication. The neural mechanisms underlying poor language outcomes in LKS are not yet understood. In this detailed functional MRI study of a recovered LKS patient - that is, a patient no longer suffering from epileptic discharges, audiovisual multi-sensory processing was investigated, since LKS patients are often proficient in reading, but not in speech perception. In the recovered LKS patient a large difference in the neural activation to auditory stimuli was found in the left versus the right auditory cortex, which cannot be attributed to hearing loss. Compared to healthy proficient readers investigated earlier with the same fMRI experiment, the patient demonstrated normal letter-sound integration in the superior temporal gyrus as demonstrated by the multi-sensory interaction index, indicating intact STG function. Diffusion Tensor Imaging (DTI) based fiber tracking in the LKS patient showed fibers originating from Heschl's gyrus that seem to be left-right inverted with respect to HG fiber pattern described in the literature for healthy controls. In the patient, in both hemispheres we found arcuate fibers projecting from (homologues of) Broca's to Wernicke's areas, and a lack of fibers from arcuate left inferior parietal and sylvian areas reported in healthy subjects. We observed short arcuate segments in the right hemisphere. Although speculative, our results suggest intact temporal lobe processing but an altered temporal to frontal connectivity. The altered connectivity might explain observed short-term verbal memory problems, disturbed (speech) sound-motor interaction and online feedback of speech and might be one of the neuronal factors underlying LKS.

Is cognition enough to explain cognitive development?

Traditional views separate cognitive processes from sensory-motor processes, seeing cognition as amodal, propositional, and compositional, and thus fundamentally different from the processes that underlie perceiving and acting. These were the ideas on which cognitive science was founded 30 years ago. However, advancing discoveries in neuroscience, cognitive neuroscience, and psychology suggests that cognition may be inseparable from processes of perceiving and acting. From this perspective, this study considers the future of cognitive science with respect to the study of cognitive development.

Music perception: information flow within the human auditory cortices

Information processing of all acoustic stimuli involves temporal lobe regions referred to as auditory cortices, which receive direct afferents from the auditory thalamus. However, the perception of music (as well as speech or spoken language) is a complex process that also involves secondary and association cortices that conform a large functional network. Using different analytical techniques and stimulation paradigms, several studies have shown that certain areas are particularly sensitive to specific acoustic characteristics inherent to music (e.g., rhythm). This chapter reviews the functional anatomy of the auditory cortices, and highlights specific experiments that suggest the existence of distinct cortical networks for the perception of music and speech.

White-matter pathways for speech and language processing

The language-relevant brain regions, Brodmann's area in the inferior frontal cortex and Wernicke's area in the superior temporal cortex, are connected via long-range fiber bundles, which are located dorsally and ventrally to the sylvian fissure. These dorsal and ventral pathways consist of a number of partly parallel-running fiber tracts, which can be differentiated by their termination regions and by the particular language functions of these termination regions. Dorsally, there are two major fiber tracts connecting the posterior temporal cortex with the frontal cortex: one terminating in the premotor cortex that subserves sensory-to-motor mapping and one terminating in posterior Broca's area, the pars opercularis, that supports the processing of complex syntactic structures. Ventrally, two language-related fiber tracts are discussed: one connects the inferior frontal cortex, i.e., the pars triangularis and orbitalis, with Wernicke's area and supports semantic processes and another one connects the most ventral portions of the inferior frontal cortex, including the frontal operculum, with the anterior temporal cortex. This latter ventral tract is suggested to subserve elementary combinatorial processes in language. Together these fiber tracts guarantee the transmission of information between different brain regions within the neural language network.

Intrahemispheric cortico-cortical connections of the human auditory cortex

The human auditory cortex comprises the supratemporal plane and large parts of the temporal and parietal convexities. We have investigated the relevant intrahemispheric cortico-cortical connections using in vivo DSI tractography combined with landmark-based registration, automatic cortical parcellation and whole-brain structural connection matrices in 20 right-handed male subjects. On the supratemporal plane, the pattern of connectivity was related to the architectonically defined early-stage auditory areas. It revealed a three-tier architecture characterized by a cascade of connections from the primary auditory cortex to six adjacent non-primary areas and from there to the superior temporal gyrus. Graph theory-driven analysis confirmed the cascade-like connectivity pattern and demonstrated a strong degree of segregation and hierarchy within early-stage auditory areas. Putative higher-order areas on the temporal and parietal convexities had more widely spread local connectivity and long-range connections with the prefrontal cortex; analysis of optimal community structure revealed five distinct modules in each hemisphere. The pattern of temporo-parieto-frontal connectivity was partially asymmetrical. In conclusion, the human early-stage auditory cortical connectivity, as revealed by in vivo DSI tractography, has strong similarities with that of non-human primates. The modular architecture and hemispheric asymmetry in higher-order regions is compatible with segregated processing streams and lateralization of cognitive functions.

Evaluation of net causal influences in the circuit responding to premotor control during the movement-readiness state using conditional Granger causality

As an initialization procedure for brain responding to subsequent movement execution (ME), the movement-readiness (MR) state is important for understanding the formation processes from daily movement training to long-term memory of movement pattern. As such, based on functional magnetic resonance imaging (fMRI), the net causal influences among regions contributing to premotor control during the MR state were explored by means of conditional Granger causality (CGC) and graph-theory methods in the present study. Our results found that net causal circuits responding to unimanual MR were identified during right-hand or left-hand MR, involving in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), upper precuneus (UPCU), caudate nucleus (CN), cingulate motor area (CMA), supplementary motor area (SMA) and primary sensorimotor area (S1M1). Moreover, the contralateral CN, SMA and S1M1 revealed greater net causal influences during unimanual MR, which highlighted the contralateral dominant modulations during unimanual MR. Furthermore, according as the graph-theory analysis, the higher In+Out degrees of upper precuneus (UPCU) during right-hand MR or higher In+Out degrees of cingulate motor area (CMA) and posterior cingulate cortex (PCC) during left-hand MR implied the brain asymmetry of causal connectivity in the circuit responding to right-hand or left-hand MR. This article is part of a Special Issue entitled SI: Brain and Memory.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions.

Granger causality network reconstruction of conductance-based integrate-and-fire neuronal systems

Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (I&F) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based I&F neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings.

Causal and structural connectivity of pulse-coupled nonlinear networks

We study the reconstruction of structural connectivity for a general class of pulse-coupled nonlinear networks and show that the reconstruction can be successfully achieved through linear Granger causality (GC) analysis. Using spike-triggered correlation of whitened signals, we obtain a quadratic relationship between GC and the network couplings, thus establishing a direct link between the causal connectivity and the structural connectivity within these networks. Our work may provide insight into the applicability of GC in the study of the function of general nonlinear networks.

Reconciling time, space and function: a new dorsal-ventral stream model of sentence comprehension

We present a new dorsal-ventral stream framework for language comprehension which unifies basic neurobiological assumptions (Rauschecker & Scott, 2009) with a cross-linguistic neurocognitive sentence comprehension model (eADM; Bornkessel & Schlesewsky, 2006). The dissociation between (time-dependent) syntactic structure-building and (time-independent) sentence interpretation assumed within the eADM provides a basis for the division of labour between the dorsal and ventral streams in comprehension. We posit that the ventral stream performs time-independent unifications of conceptual schemata, serving to create auditory objects of increasing complexity. The dorsal stream engages in the time-dependent combination of elements, subserving both syntactic structuring and a linkage to action. Furthermore, frontal regions accomplish general aspects of cognitive control in the service of action planning and execution rather than linguistic processing. This architecture is supported by a range of existing empirical findings and helps to resolve a number of theoretical and empirical puzzles within the existing dorsal-ventral streams literature.

Longitudinal Heschl's gyrus growth during childhood and adolescence in typical development and autism

Heightened auditory sensitivity and atypical auditory processing are common in autism. Functional studies suggest abnormal neural response and hemispheric activation to auditory stimuli, yet the neurodevelopment underlying atypical auditory function in autism is unknown. In this study, we model longitudinal volumetric growth of Heschl's gyrus gray matter and white matter during childhood and adolescence in 40 individuals with autism and 17 typically developing participants. Up to three time points of magnetic resonance imaging data, collected on average every 2.5 years, were examined from individuals 3-12 years of age at the time of their first scan. Consistent with previous cross-sectional studies, no group differences were found in Heschl's gyrus gray matter volume or asymmetry. However, reduced longitudinal gray matter volumetric growth was found in the right Heschl's gyrus in autism. Reduced longitudinal white matter growth in the left hemisphere was found in the right-handed autism participants. Atypical Heschl's gyrus white matter volumetric growth was found bilaterally in the autism individuals with a history of delayed onset of spoken language. Heightened auditory sensitivity, obtained from the Sensory Profile, was associated with reduced volumetric gray matter growth in the right hemisphere. Our longitudinal analyses revealed dynamic gray and white matter changes in Heschl's gyrus throughout childhood and adolescence in both typical development and autism.

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI

A number of previous studies have examined music-related plasticity in terms of multi-sensory and motor integration but little is known about the functional and effective connectivity patterns of spontaneous intrinsic activity in these systems during the resting state in musicians. Using functional connectivity and Granger causal analysis, functional and effective connectivity among the motor and multi-sensory (visual, auditory and somatosensory) cortices were evaluated using resting-state functional magnetic resonance imaging (fMRI) in musicians and non-musicians. The results revealed that functional connectivity was significantly increased in the motor and multi-sensory cortices of musicians. Moreover, the Granger causality results demonstrated a significant increase outflow-inflow degree in the auditory cortex with the strongest causal outflow pattern of effective connectivity being found in musicians. These resting state fMRI findings indicate enhanced functional integration among the lower-level perceptual and motor networks in musicians, and may reflect functional consolidation (plasticity) resulting from long-term musical training, involving both multi-sensory and motor functional integration.

The cortical language circuit: from auditory perception to sentence comprehension

Over the years, a large body of work on the brain basis of language comprehension has accumulated, paving the way for the formulation of a comprehensive model. The model proposed here describes the functional neuroanatomy of the different processing steps from auditory perception to comprehension as located in different gray matter brain regions. It also specifies the information flow between these regions, taking into account white matter fiber tract connections. Bottom-up, input-driven processes proceeding from the auditory cortex to the anterior superior temporal cortex and from there to the prefrontal cortex, as well as top-down, controlled and predictive processes from the prefrontal cortex back to the temporal cortex are proposed to constitute the cortical language circuit.

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models

PURPOSE

This fMRI study is about modelling the effective connectivity between Heschl's gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. MATERIALS #ENTITYSTARTX00026;

METHODS

Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity.

RESULTS

Group results indicated significant asymmetrical activation (p(uncorr) < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself.

CONCLUSION

We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.

Dissociable neural imprints of perception and grammar in auditory functional imaging

In language processing, the relative contribution of early sensory and higher cognitive brain areas is still an open issue. A recent controversial hypothesis proposes that sensory cortices show sensitivity to syntactic processes, whereas other studies suggest a wider neural network outside sensory regions. The goal of the current event-related fMRI study is to clarify the contribution of sensory cortices in auditory syntactic processing in a 2 × 2 design. Two-word utterances were presented auditorily and varied both in perceptual markedness (presence or absence of an overt word category marking "-t"), and in grammaticality (syntactically correct or incorrect). A multivariate pattern classification approach was applied to the data, flanked by conventional cognitive subtraction analyses. The combination of methods and the 2 × 2 design revealed a clear picture: The cognitive subtraction analysis found initial syntactic processing signatures in a neural network including the left IFG, the left aSTG, the left superior temporal sulcus (STS), as well as the right STS/STG. Classification of local multivariate patterns indicated the left-hemispheric regions in IFG, aSTG, and STS to be more syntax-specific than the right-hemispheric regions. Importantly, auditory sensory cortices were only sensitive to the overt perceptual marking, but not to the grammaticality, speaking against syntax-inflicted sensory cortex modulations. Instead, our data provide clear evidence for a distinction between regions involved in pure perceptual processes and regions involved in initial syntactic processes.

A short history of causal modeling of fMRI data

Twenty years ago, the discovery of the blood oxygen level dependent (BOLD) contrast and invention of functional magnetic resonance imaging (MRI) not only allowed for enhanced analyses of regional brain activity, but also laid the foundation for novel approaches to studying effective connectivity, which is essential for mechanistically interpretable accounts of neuronal systems. Dynamic causal modeling (DCM) and Granger causality (G-causality) modeling have since become the most frequently used techniques for inferring effective connectivity from fMRI data. In this paper, we provide a short historical overview of these approaches, describing milestones of their development from our subjective perspectives.

The brain basis of language processing: from structure to function

Language processing is a trait of human species. The knowledge about its neurobiological basis has been increased considerably over the past decades. Different brain regions in the left and right hemisphere have been identified to support particular language functions. Networks involving the temporal cortex and the inferior frontal cortex with a clear left lateralization were shown to support syntactic processes, whereas less lateralized temporo-frontal networks subserve semantic processes. These networks have been substantiated both by functional as well as by structural connectivity data. Electrophysiological measures indicate that within these networks syntactic processes of local structure building precede the assignment of grammatical and semantic relations in a sentence. Suprasegmental prosodic information overtly available in the acoustic language input is processed predominantly in a temporo-frontal network in the right hemisphere associated with a clear electrophysiological marker. Studies with patients suffering from lesions in the corpus callosum reveal that the posterior portion of this structure plays a crucial role in the interaction of syntactic and prosodic information during language processing.

Neural correlates of interindividual differences in children's audiovisual speech perception

Children use information from both the auditory and visual modalities to aid in understanding speech. A dramatic illustration of this multisensory integration is the McGurk effect, an illusion in which an auditory syllable is perceived differently when it is paired with an incongruent mouth movement. However, there are significant interindividual differences in McGurk perception: some children never perceive the illusion, while others always do. Because converging evidence suggests that the posterior superior temporal sulcus (STS) is a critical site for multisensory integration, we hypothesized that activity within the STS would predict susceptibility to the McGurk effect. To test this idea, we used BOLD fMRI in 17 children aged 6-12 years to measure brain responses to the following three audiovisual stimulus categories: McGurk incongruent, non-McGurk incongruent, and congruent syllables. Two separate analysis approaches, one using independent functional localizers and another using whole-brain voxel-based regression, showed differences in the left STS between perceivers and nonperceivers. The STS of McGurk perceivers responded significantly more than that of nonperceivers to McGurk syllables, but not to other stimuli, and perceivers' hemodynamic responses in the STS were significantly prolonged. In addition to the STS, weaker differences between perceivers and nonperceivers were observed in the fusiform face area and extrastriate visual cortex. These results suggest that the STS is an important source of interindividual variability in children's audiovisual speech perception.

Using spatial multiple regression to identify intrinsic connectivity networks involved in working memory performance

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship.